Side, a seasoned services provider, has entered into a six‑month memorandum of understanding with Denmark‑based artificial‑intelligence specialist Modl.ai to co‑develop an AI‑powered quality‑assurance (QA) platform for the games industry. The partnership blends Side’s deep‑rooted expertise in service delivery with Modl.ai’s cutting‑edge AI capabilities, aiming to create a solution that can augment traditional QA processes while keeping human oversight at the core. Side, formerly known as PTW, has long been a fixture in the outsourcing and testing arena. Modl.ai, by contrast, is a relatively new player that broke into the gaming market in 2018 and secured $1.7 million in seed funding two years later.
According to Martin McBride, Side’s chief commercial officer, the MOU “effectively brings the best of what Side has and the best of what Modl.ai has together in a unique solution.” He adds that the industry’s “holy grail” has been to harness AI to enhance QA services, a goal that many have pursued without finding a robust, scalable answer. Side believes the new collaboration finally delivers that answer. Earlier AI‑driven QA tools, including Modl.ai’s first‑generation offering, required developers to ship entire builds or even share source code with the testing vendor. This “integration‑based” model relied on plugins and software development kits (SDKs) that created considerable friction and, as founder Christoffer Holmgard notes, became increasingly unwieldy over time.
The next‑generation system being built under the MOU eliminates the need for any internal access to the game’s code or assets. Instead, the product is treated exactly as a QA tester—or ultimately a consumer—would receive it.
Holmgard explains the workflow: the game is installed on a device that mirrors the target platform, and the AI watches the screen, simulates player inputs, and records every observable event. This raw data set is then handed off to a second AI layer that scans for anomalies, flags potential bugs, and escalates findings to a human reviewer for final validation.
The process begins with what Modl.ai calls “building game knowledge.” Developers upload assets, design documents, screenshots, or any other relevant material and converse with the AI in natural language to teach it the specifics of their title. “All of this is in natural language,” Holmgard says. “We just chat with the system about our game, but we’re also adding images, design docs, and so on.” Once the AI has a baseline understanding, developers specify the testing objectives. These can range from classic test cases—such as verifying menu navigation or level loading—to novel scenarios that are better suited to AI‑driven exploration.
Holmgard stresses that human expertise remains essential at this stage to craft effective prompts and guide the AI toward the right behaviours. The AI then executes the defined sessions, producing comprehensive bug reports that include textual descriptions, short video clips (referred to as “evidence”), and full log data. These reports are reviewed by seasoned QA specialists who decide how to act on each finding. A persistent challenge in automated testing is distinguishing a genuine bug from an intentional feature.
Holmgard points out that continuous feedback from human testers helps the AI refine its judgment. “Some of it comes from the prompting, some from the game knowledge you built up beforehand, and a good part comes from feedback over time from the human testers,” he says. Over successive cycles, the system becomes attuned to the nuances of each game’s design philosophy.
Side envisions a broader shift in the QA workforce as AI takes over repetitive, low‑value tasks. McBride explains that this opens a pathway for QA staff to evolve into “AI engineers,” moving up the value chain and earning higher salaries. By elevating the role of testers, Side hopes to bring jobs back to regions where they have previously migrated due to cost pressures. “Instead of a career that stops at senior tester, people can become AI engineers, get paid more, and we can repatriate talent to countries that lost it,” he notes.
The AI tool also promises a more fulfilling career for existing QA professionals. By automating smoke tests, regression checks, and other routine verifications, testers can focus on strategic analysis, creative testing, and gameplay assessment. Benedikte Mikkelsen, Modl.ai’s chief product officer, adds that eliminating tedious, repetitive flows frees human talent to concentrate on higher‑order tasks such as evaluating game feel and designing novel test scenarios. This, she argues, is the core value proposition of AI‑augmented QA.
Despite the optimism, both companies stress that AI will never fully replace human QA workers. The price point for manual testing in certain low‑cost regions remains too low to eliminate the need for human involvement entirely.
However, by providing advanced tooling, Side can extend careers, retain talent longer, and improve overall quality. “There will always be an opportunity for people to do a lot of the testing work because the price point of testing right now is so low in certain countries that it’s very hard to augment it completely away,” McBride says. “But by giving our people tool sets like this, I’m allowing them to further their career.” McBride also describes Side’s philosophy on AI as a “sliding scale” – a spectrum where automation and human input coexist. “There will always be a human in the loop—that’s our ethos,” he asserts.
By leveraging AI to reduce human error and fatigue, the overall QA process becomes more reliable and efficient. When asked about the types of games the solution currently supports, COO Oliver Deslandes admits that the technology is best suited for simpler titles—puzzle games, card games, and other experiences with repeatable mechanics.
Fast‑paced, graphically intensive 3D open‑world or fighting games remain a longer‑term goal. Deslandes emphasizes that early adopters need to be willing to experiment and accept that the solution will evolve alongside their needs.
“It’s a journey,” he says. “If you’re at the table now and maybe doing some pilots with us, you’ll see where this tech goes.” In summary, the Side‑Modl.ai partnership seeks to blend AI’s speed and consistency with human expertise, creating a hybrid QA model that reduces repetitive work, improves bug detection, and opens new career pathways for testers. The six‑month MOU marks the first step toward a future where AI acts as a powerful assistant rather than a replacement, ensuring that quality assurance remains both rigorous and adaptable as the gaming industry continues to evolve.